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Long-term exposure to high concentrations of fine particles can cause irreversible damage to people's health. Therefore, it is of extreme significance to conduct large-scale continuous spatial fine particulate matter (PM2.5) concentration prediction for air pollution prevention and control in China. The distribution of PM2.5 ground monitoring stations in China is uneven with a larger number of stations in southeastern China, while the number of ground monitoring sites is also insufficient for air quality control. Remote sensing technology can obtain information quickly and macroscopically. Therefore, it is possible to predict PM2.5 concentration based on multi-source remote sensing data. Our study took China as the research area, using the Pearson correlation coefficient and GeoDetector to select auxiliary variables. In addition, a long short-term memory neural network and random forest regression model were established for PM2.5 concentration estimation. We finally selected the random forest regression model (R2 = 0.93, RMSE = 4.59 μg m−3) as our prediction model by the model evaluation index. The PM2.5 concentration distribution across China in 2021 was estimated, and then the influence factors of high-value regions were explored. It is clear that PM2.5 concentration is not only related to the local geographical and meteorological conditions, but also closely related to economic and social development. [ABSTRACT FROM AUTHOR]

Grassland desertification stands as an ecological concern globally. It is crucial for desertification prevention and control to comprehend the variation in area and severity of desertified grassland (DGL), clarify the intensities of conversion among DGLs of different desertification levels, and explore the spatial and temporal driving factors of desertification. In this study, a Desertification Difference Index (DDI) model was constructed based on albedo-EVI to extract desertification information. Subsequently, intensity analysis, the Geo-detector model, and correlation analysis were applied to analyze the dynamics and driving factors of desertification. The results showed the following: (1) Spatially, the DGL in Xilingol exhibited a zonal distribution. Temporally, the degree of DGL decreased, with the proportion of severely and moderately desertified areas decreasing from 51.77% in 2000 to 37.23% in 2020, while the proportion of nondesertified and healthy areas increased from 17.85% in 2000 to 37.40% in 2020; (2) Transition intensities among different desertification levels were more intense during 2000–2012, stabilizing during 2012–2020; (3) Meteorological factors and soil conditions primarily drive the spatial distribution of DDI, with evapotranspiration exhibiting the most significant influence (q-value of 0.83), while human activities dominate interannual DDI variations. This study provides insights into the conversion patterns among different desertification levels and the divergent driving forces shaping desertification in both spatial and temporal dimensions in Xilingol. [ABSTRACT FROM AUTHOR]

Tang Luo Ning (TLN), a traditional Chinese compound prescription, has been used clinically to treat diabetic peripheral neuropathy (DPN) in China. However, the exact mechanisms remain unclear. The objective of this study is to unravel the effects of TLN on mitochondrial dynamics of DPN in streptozotocin-induced rat models and Schwann cells cultured in 150 mM glucose. Mitochondrial function was determined by Ca2+ and ATP levels of streptozotocin (STZ)-induced DPN rats and mitochondria structure, mitochondrial membrane potential (MMP), and mtDNA of high glucose incubated SCs. Mitochondrial dynamics protein including mitofusin 1 (Mfn1), mitofusin 2 (Mfn2), optic atrophy 1 (Opa1), and dynamin-related protein 1 (Drp1) were investigated using Western blot or immunofluorescence. Myelin basic protein (MBP), myelin protein zero (MPZ), and sex-determining region Y (SRY)-box 10 (Sox10) were measured to represent schwannopathy. Our results showed that TLN increased ATP levels (0.38 of model, 0.69 of HTLN, 0.61 of LTLN, P ＜0.01; 0.52 of 150 mM glucose, 1.00 of 10% TLN, P ＜0.01, 0.94 of 1% TLN, P ＜0.05), MMP (0.56 of 150 mM glucose, P ＜0.01, 0.75 of 10% TLN, P ＜0.05, 0.83 of 1% TLN, P ＜0.01), and mtDNA (0.32 of 150 mM glucose, 0.43 of 10% TLN, P ＜0.01) while decreased Ca2+ (1.54 of model, 1.06 of HTLN, 0.96 of LTLN, P ＜0.01) to improve mitochondrial function in vivo and in vitro. TLN helps maintain balance of mitochondrial dynamics: it reduces the mitochondria number (1.60 of 150 mM glucose, 1.10 of 10% TLN, P ＜0.01) and increases the mitochondria coverage (0.51 of 150 mM glucose, 0.80 of 10% TLN, 0.87 of 1% TLN, P ＜0.01), mitochondrial network size (0.51 of 150 mM glucose, 0.95 of 10% TLN, 0.94 of 1% TLN, P ＜0.01), and branch length (0.63 of 150 mM glucose, P ＜0.01, 0.73 of 10% TLN, P ＜0.05, 0.78 of 1% TLN, P ＜0.01). Further, mitochondrial dynamics–related Mfn1 (0.47 of model, 0.82 of HTLN, 0.77 of LTLN, P ＜0.01; 0.42 of 150 mM glucose, 0.56 of 10% TLN, 0.57 of 1% TLN, P ＜0.01), Mfn2 (0.40 of model, 0.84 of HTLN, 0.63 of LTLN, P ＜0.01; 0.46 of 150 mM glucose, 1.40 of 10% TLN, 1.40 of 1% TLN, P ＜0.01), and Opa1 (0.58 of model, 0.71 of HTLN, 0.90 of LTLN, P ＜0.01; 0.69 of 150 mM glucose, 0.96 of 10% TLN, 0.98 of 1% TLN, P ＜0.05) were increased, while Drp1 (1.39 of model, 0.96 of HTLN, 1.18 of LTLN, P ＜0.01; 1.70 of 150 mM glucose, 1.20 of 10% TLN, 1.10 of 1% TLN, P ＜0.05), phosphorylated Drp1 (2.61 of model, 1.44 of HTLN, P ＜0.05; 2.80 of 150 mM glucose, 1.50 of 10% TLN, 1.30 of 1% TLN, P ＜0.01), and Drp1 located in mitochondria (1.80 of 150 mM glucose, 1.00 of 10% TLN, P ＜0.05) were decreased after treatment with TLN. Additionally, TLN improved schwannopathy by increasing MBP (0.50 of model, 1.05 of HTLN, 0.94 of HTLN, P ＜0.01; 0.60 of 150 mM glucose, 0.78 of 10% TLN, P ＜0.01, 0.72 of 1% TLN, P ＜0.05), Sox101 (0.41 of model, 0.99 of LTLN, P ＜0.01; 0.48 of 150 mM glucose, 0.65 of 10% TLN, P ＜0.05, 0.69 of 1% TLN, P ＜0.01), and MPZ (0.48 of model, 0.66 of HTLN, 0.55 of HTLN, P ＜0.01; 0.60 of 150 mM glucose, 0.78 of 10% TLN, P ＜0.01, 0.75 of 1% TLN, P ＜0.05) expressions. In conclusion, our study indicated that TLN's function on DPN may link to the improvement of the mitochondrial dynamics, which provides scientific evidence for the clinical application. [ABSTRACT FROM AUTHOR]

This paper reviews the studies on dynamic distributed transmission and distribution system and traditional heating distribution system in aspects of mathematical model, structure of pipe network, hydraulic stability of the dynamic distributed system and regulation and control strategy; comparatively analyses the characteristics and difference between each kind of system and summaries the progress and deficiency of existing researches. It is remarkable that pumps should be equipped with various frequency devices to achieve the optimal energy saving effects and regulating efficiency. Many achievements have been realized in each aspect, but there are still disadvantages in the dynamic distributed heating system. All the deficiencies will be the research directions about the dynamic distributed heating system in the future. [ABSTRACT FROM AUTHOR]

The complexes of historic timber-structure buildings are extremely complicated and have various fire threats. A targeted approach to fire risk assessment of historic timber structures is conducive to focused fire plans. Due to the sparsity of the historical fire event dataset, it is quite challenging to predict the fire risk of heritage buildings based on historical fire events data. In this study, a fire risk index-driven solution is proposed based on machine learning to predict the fire risk level of timber heritage buildings. The suggested fire risk index system emphasizes the specificities of timber and historic structures, and the indicators are processed on temporal, spatial, and attribute scales. Considering the uncertainty of fire risk, this approach objectively rates the historical fire risk of heritage buildings using entropy-weighted TOPSIS. The typical machine learning model, XGBoost, is enhanced by applying the spatially unique values to predict the monthly fire risk level of a single heritage building. It solves the issue that general models only take into account the attribute characteristics of heritage buildings. Through the proposed solution, the monthly fire risk level of the heritage buildings of the Palace Museum of China in 2019 was assessed by the XGBoost model using the fire risk index data of the historical years (2016–2018). The accuracy evaluation showed that XGBoost performed better than other models (GBDT, CatBoost, Adaboost, and SVM), which is expected to provide information support for the safety inspection work of the fire department in the Palace Museum. [ABSTRACT FROM AUTHOR]

• Ten factors were chosen for assessing the risk of vegetation change. • The random forest model was employed to invert above-ground biomass. • The Mann-Kendall method was utilized to compute above-ground biomass trends, indicating vegetation degradation. • Bayesian Network enhanced the reliability and efficiency of vegetation change risk assessment. • The spatial and temporal distribution and trend of vegetation change risk in Xilin Gol League were analyzed. As an essential ecological barrier in the north of China, the grassland degradation situation in the Xilin Gol League of Inner Mongolia has remained severe in recent years. Based on data spanning from 2010 to 2022, this study utilizes a set of ten indicators, encompassing altitude, temperature, precipitation, wind speed, FVC, LAI, FRAR, NPP, ET, and above-ground biomass, to construct a Bayesian model for assessing ecological risks associated with vegetation change in the Xilin Gol League. In the case of the most crucial parameter, above-ground biomass, we integrate spectral bands, vegetation indices, and ground-truth data, employing the Random Forest algorithm to estimate the above-ground biomass in the Xilin Gol League. The study further applies the Mann-Kendall trend test and Sen's slope estimation to analyze changes in this parameter and employs it as an indicator for assessing grassland degradation. The results showed that (1) Overall, the risk level decreases gradually from the west to the east and aligns with the grassland types of the Xilin Gol League. (2) In terms of spatial and temporal distribution, medium and high-risk areas are primarily located in the western region of the Xilin Gol League, showing a distinct westward shift from 2010 to 2022. (3) Areas with higher grassland degradation risk are characterized by lower altitudes, higher temperatures, less precipitation, lower vegetation coverage, and reduced potential evapotranspiration. (4) Under the pressures of both climate warming and vegetation change, there has been a significant shift in grassland degradation risk levels in the Xilin Gol League. The application of the Bayesian model effectively reveals intricate causal relationships among various variables, such as climate, terrain, and vegetation dynamics. This study could provide guidance for the prevention and control of grassland degradation in the Xilin Gol League. [ABSTRACT FROM AUTHOR]

Background: Intrahepatic recurrence is a significant problem for patients who have undergone a hepatic resection for hepatocellular carcinoma (HCC). The objective of the present study was to identify risk factors and evaluate the management of early and late recurrence of solitary HCC after curative resection., Methods: Included in this study were 816 patients with solitary HCC who underwent a curative partial hepatectomy. Intrahepatic recurrence in these patients was followed up retrospectively. Prognosis and therapy for the recurrence were investigated and analysed., Results: Early and late intrahepatic recurrence occurred in 423 patients and 199 patients, respectively. Multivariate analysis showed that a tumour diameter >5 cm, the absence of a tumour capsule and the presence of microvascular invasion were correlated with early recurrence, whereas cirrhosis and alpha-fetal protein >400 μg/l were independent risk factors contributing to late recurrence. The 5-year survival of HCC patients with early recurrence was significantly lower than that of patients with late recurrence. Further curative treatment for intrahepatic recurrence offered a 5-year overall survival of 56.0%, which was better than alternative management., Conclusion: Early and late recurrences of solitary HCC after curative resection are associated with different predictive factors. The time to recurrence and further curative treatment after recurrence were the best predictors of survival post recurrence., (© 2014 International Hepato-Pancreato-Biliary Association.)